Akhilan Boopathy
9 papers · 2019–2025 · 4 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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🌍 Conference Polyglot · Bronze 🏃 Academic Marathon · Sprint 🗺️ Taxonomy Completionist (19) 🐣 Hot Topic Early Bird 🔥 Unstoppable · Bronze
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Conference Pioneer
Top co-authors
Research topics
Machine Learning
(9)
Optimization & Theory · Machine Learning
(6)
Artificial Intelligence
(5)
Deep Learning
(5)
Architectures
(3)
Core AI
(3)
Learning Paradigms
(2)
Learning Types · Machine Learning
(2)
Optimization & Theory · Deep Learning
(2)
Techniques
(2)
Application Areas
(1)
Core Methods
(1)
Learning Types · Deep Learning
(1)
Keywords
adversarial robustness
(4)
neural network
(3)
information theory
(2)
inductive bia
(2)
robust optimization
(1)
lower bound
(1)
learning theory
(1)
formal verification
(1)
catastrophic forgetting
(1)
gradient descent
(1)
adversarial attack
(1)
convolutional neural network
(1)
sample complexity
(1)
neural network verification
(1)
scaling law
(1)
robust classification
(1)
neural network robustness
(1)
grid cell
(1)
certified defense
(1)
neural tangent kernel
(1)
Papers
Breaking Neural Network Scaling Laws with Modularity
ICLR 2025
Rapid Learning without Catastrophic Forgetting in the Morris Water Maze
ICML 2024
Towards Exact Computation of Inductive Bias
IJCAI 2024
Model-agnostic Measure of Generalization Difficulty
ICML 2023
How to Train Your Wide Neural Network Without Backprop: An Input-Weight Alignment Perspective
ICML 2022
Fast Training of Provably Robust Neural Networks by SingleProp
AAAI 2021
Proper Network Interpretability Helps Adversarial Robustness in Classification
ICML 2020
CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks
AAAI 2019
PROVEN: Verifying Robustness of Neural Networks with a Probabilistic Approach
ICML 2019